Weather can have a significant impact on local economies, and sometimes different impacts on segments of the same economy. For instance, major weather events such as hurricanes and tornados can have a powerful negative impact on a devastated economy, but normal weather trends and variances can have a marked impact as well. For instance, greater than or less than normal rain fall or temperatures can effect crop yields and effect participation in outdoor activities, and businesses directed tied to these activities will be effected. Additionally, other businesses can be affected by the secondary effects of a strengthened or weakened economy. Understanding these direct and secondary effects is a labor intensive, often less than accurate and costly effort involving multiple sources, disparate computer systems, costly economic and weather models and a deep understanding of the local businesses, as well as the interconnections and interrelatedness of businesses. In the end, it is often the gut feeling of people long experienced in a local or larger economy who can explain the impact of weather of a limited market or local economy by under qualified indicators, such as simply saying the economy is or is going to be “strong” or “weak” based on experience rather than solid numbers or analytics. Further, the resulting analysis of more quantitative analysis may not be readily understandable to many participants in an economy that might be benefited by such knowledge without significant training.
Further, such significant efforts of obtaining the expertise, conducting the analysis and educating those who could benefit in interpreting the results from such insights cannot be justified or are unavailable though these insights could be of great value. This is particularly evident for medium to small businesses and those that serve them. For instance, small lending institutions in rural communities lack such resources. As a more extreme example, institutions that provide micro-financing require a business model that has very low transaction costs. This often means employing relatively low skilled, low cost employees, using simple business arrangements and adopting readily understood criteria for determining what a given transaction's parameters (e.g., interest rates, payback period, collateral, etc.) should be. Micro-finance customers located in rural and heavily agricultural geographies who rely upon agriculture for income are usually directly affected by weather, which can impact their ability and timing of their repayments for a given growing season. For example, snow storms may have impact on the crop yield of the next year, the crop price, the annual income of the micro-finance customers, and eventually their ability to timely repay the interest and/or the principal of the loans. Lenders of such loans, therefore, may need to manage the loan to ensure the repayment by adjusting loan parameters and/or proactively intervening before the micro-finance customer defaults.
As such, there is a need for a technical solution to provide an efficient analysis of a vast amount of transaction data, weather data, and demographic data to calculate an index value to indicate the impact of weather on the financial conditions of an economy or market and the participants therein.